Two Reproductions of a Human-Assessed Comparative Evaluation of a Semantic Error Detection System
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3A10457002" target="_blank" >RIV/00216208:11320/22:10457002 - isvavai.cz</a>
Result on the web
<a href="https://aclanthology.org/2022.inlg-genchal.9/" target="_blank" >https://aclanthology.org/2022.inlg-genchal.9/</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Two Reproductions of a Human-Assessed Comparative Evaluation of a Semantic Error Detection System
Original language description
In this paper, we present the results of two reproduction studies for the human evaluation originally reported by Dušek and Kasner (2020) in which the authors comparatively evaluated outputs produced by a semantic error detection system for data-to-text generation against reference outputs. In the first reproduction, the original evaluators repeat the evaluation, in a test of the repeatability of the original evaluation. In the second study, two new evaluators carry out the evaluation task, in a test of the reproducibility of the original evaluation under otherwise identical conditions. We describe our approach to reproduction, and present and analyse results, finding different degrees of reproducibility depending on result type, data and labelling task. Our resources are available and open-sourced.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 15th International Conference on Natural Language Generation: Generation Challenges
ISBN
978-1-955917-60-5
ISSN
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e-ISSN
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Number of pages
10
Pages from-to
52-61
Publisher name
Association for Computational Linguistics
Place of publication
Stroudsburg, PA, USA
Event location
Waterville, ME, USA
Event date
Jul 18, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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